gu-mi

# A simple approach to visually-weighted regression plots

doInstall <- TRUE  # Change to FALSE if you don't want packages installed.
toInstall <- c("ggplot2", "reshape2", "MASS")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

# Generate some data:
nn <- 1000
myData <- data.frame(X = rnorm(nn),

gu-mi

## I came across a Chinese science blog which discusses an interesting stuff that girls should reject 
## the first 37% (for 1/e = 36.79%) pursuers in her life. A little R simulation as outlined in the 
## gist is shown below just for fun. In the snippet, m is the total number of boys you can choose. 
## In other words, they are potential husband for you. Larger number means high "quality" but these 
## numbers are randomly sampled, i.e., you don’t know whether the one who just walks into your life 
## is your Mr. Right or not. You reject the first m/e people (probably without any reason...), where 
## e is the Euler’s number, and choose from the rest of the m people. If you find any one of the 
## remaning boys better than the best boy you saw earlier in the first m/e ones, then you choose that 
## guy; otherwise, you have to make do with the last guy for the rest of your life...

gu-mi

# Note: using the devel versions of both packages!
library(DESeq) # version 1.9.11
library(edgeR) # version 2.99.8
library(VennDiagram)

# Read in data ------------------------------------------------------------

## Use pasilla data
datafile = system.file( "extdata/pasilla_gene_counts.tsv", package="pasilla" )
datafile